Predictive fault tolerance in multiagent systems: a plan-based replication approach

ABSTRACT

The fact that multiagent applications are prone to the same faults that any distributed system is susceptible to and the need for a higher quality of service in these systems justify the increasing interest in fault-tolerant multiagent systems. In this article, we propose an original method for providing dependability in multiagent systems through replication. Our method is different from other works because our research focuses on building an automatic, adaptive and predictive replication policy where critical agents are replicated to minimize the impact of failures. This policy is determined by taking into account the criticality of the plans of the agents, which contain the collective and individual behaviors of the agents in the application. The set of replication strategies applied at a given moment to an agent is then fine-tuned gradually by the replication system so as to reflect the dynamicity of the multiagent system. Some preliminary measurements were made to assess the efficiency of our approach and future directions are presented.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
        I.2.11 Distributed Artificial Intelligence
            Subjects: Multiagent systems

General Terms:
Algorithms, Experimentation, Performance, Reliability

Keywords:
adaptation, agent, criticality, fault tolerance, multiagent system, plan, replication